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Bayesian option pricing using asymmetric GARCH

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Author Info

  • BAUWENS, LUC

    ()
    (Center for Operations Research and Econometrics (CORE), Université catholique de Louvain (UCL), Louvain la Neuve, Belgium)

  • LUBRANO, Michel

    ()
    (GREQAM, CNRS)

Abstract

This paper shows how one can compute option prices from a Bayesian inference viewpoint, using an econometric model for the dynamics of the return and of the volatility of the underlying asset. The proposed evaluation of an option is the predictive expectation of its payoff function. The predictive distribution of this function provides a natural metric with respect to which the predictive option price, or other option evaluations, can be gauged. The proposed method is compared to the Black and Scholes evaluation, in which a predictive mean volatility is plugged, but which does not provide a natural metric. The methods are illustrated using an asymmetric GARCH model with a data set on a stock index in Brussels. The persistence of the volatility process is linked to the prediction horizon and to the option maturity.

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Bibliographic Info

Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 1997059.

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Date of creation: 01 Aug 1997
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Handle: RePEc:cor:louvco:1997059

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Related research

Keywords: Bayesian; GARCH; option pricing; simulation;

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Cited by:
  1. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
  2. HAFNER, Christian & HERWARTZ, Helmut, 2001. "Volatility impulse response functions for multivariate GARCH models," CORE Discussion Papers 2001039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.

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